| Zugriffsnummer | 17942 |
| Dokumenttyp | Konferenzartikel |
| Sprache | Englisch |
| Titel | Scattering effects on room acoustics quality: Evaluation for a case study |
| Autor(in); Institution |
Ribeiro, Maria Rosa S.aacute.; FEUP, Porto, PORTUGAL
Martins, Fernando Gomes; FEUP, Porto, PORTUGAL
Bork, Ingolf; 1.7, Angewandte Akustik, PTB-Braunschweig
|
| Quelle/Jahr | Forum Acusticum Budapest, 29 Aug - 2 Sep 2005: Proceedings : [Acoustics: science and technology for knowledge based society and healthy environment]:(2005), 2135 - 2140 |
| Availability | [CD-ROM] ; file name: 202-0.pdf |
| Herausgeber(in) |
Augusztinovicz, Fülöp
|
| ISBN | 963-8241-68-3 |
| Verlag | Budapest: OPAKFI |
| Konferenzangaben | Congress Forum Acusticum, Budapest, 29, August - 02, September, 2005, Hungary |
| Zusammenfassung | Room acoustic quality is known to be dependent on diffusion properties of interior surfaces. How reflected sound is distributed from each surface into non specular directions and how much scattered energy is addressed to listeners are two essential features for good acoustics. Although assessing halls diffusion is very difficult, there are some methods, based on a surface diffusion index (SDI), as a measure of surface irregularities visually assessed from drawings and photos, using several criteria. Values have been related with an acoustical quality index (AQI) as a function of the averaged subjective evaluation of halls. Objective information from the definition of a diffusion coefficient together with a scattering coefficient is now available for professionals with different backgrounds and different areas of interest. Methods of measuring these coefficients are being standardized, but only few values are available in literature. Neural networks have proved to be a successful tools to estimate the acoustical parameters within the subjective limens, and a strong correlation between SDI and AQI was found using only geometrical data. Trying to further understand these concepts, measured parameters and calculated values from prediction software, using different scattering coefficients are compared for a particular case. This paper also reports a neural network approach to predict the same parameters and to estimate SDI from geometrical and acoustical data. The results achieved are compared with assessments known from literature and also from a small group of people with different levels of practical experience on architecture, music and acoustics. |
